Modern data-intensive applications require the transfer of big data over high-performance networks (HPNs) through bandwidth reservation for various purposes such as data storage and analysis. The key performance metrics for bandwidth scheduling include the utilization of network resources and the satisfaction of user requests. In this paper, for a given batch of Deadline-Constrained Bandwidth Reservation Requests (DCBRRs), we attempt to maximize the number of satisfied requests with flexible scheduling options over link-disjoint paths in an HPN while achieving the best average Earliest Completion Time (ECT) or Shortest Duration (SD) of scheduled requests. We further consider this problem from two bandwidth-oriented principles: (i) Minimum Bandwidth Principle (MINBP), and (ii) Maximum Bandwidth Principle (MAXBP). We show that both of these problem variants are NP-complete, and propose two heuristic algorithms with polynomial-time complexity for each. We conduct bandwidth scheduling experiments on both small-and large-scale DCBRRs in a real-life HPN topology for performance comparison. Extensive results show the superiority of the proposed algorithms over existing ones in comparison.